Supplementary Material - Base model assumptions
Introduction
Methods
Example interpretation of EE
How to interpret results
Results
Body Weight
Change in Male Body Weight input assumptions
Changes in base model assumptions for body weight alters how change in energy imbalance impacts BMI category prevalence estimates. The figure below shows the elementary effect for each local sensitivity analysis change Male assumptions body weight assumptions.
- Changes in the underweight and healthy weight body weight assumptions reducing the sensitivity of the model, where higher assumed body weight reduces the flow into overweight creating a lower overweight BMI % and higher underweight/ health weight BMI %.
- Similarly, higher body weight for obesity cohorts reduces the prevalence at the of the model, and increases the prevalence for overweight outcomes.
- Younger ages impact the BMI outcomes for all older age groups, with the largest impact on the age groups being altered.
- Older age groups do not impact younger outcomes.
- Changes in each BMI categories mainly impacts the outcome of the BMI
category being changed and the neighboring BMI category.
- Assumptions in Healthy weight impacts the underweight and healthy weight and overweight outcome, however has minimal impact on with obesity outcome.
- Change in the assumptions for overweight main impact the outcome for all BMI category
- Changing the Obesity assumptions change the obesity and overweight outcomes
Change in Female Body Weight input assumptions
There are similar relationships as noted in the male assumptions.
Additionally;
- The results show that the intergenerational effects.
- Changes in the female assumptions has a slight impact in younger male age group.
- Larger changes in female outcomes, results in lager impacts in
younger age groups.
- Changes in the high fertility age groups results in proportionally
higher change in younger age groups.
- Change in body weight assumptions for Age 2 peaked at average slope of 15 %/kg resulting in 0.5 %/kg changes in young males, 3.3% of the effect was transferred.
- Change in body weight assumptions for Age 20 24 peaked at 1 %/kg resulting in a 0.1%/kg change in young males, 10% of the effect was transferred.
- Changes in the high fertility age groups results in proportionally
higher change in younger age groups.
Height
Similar to changes in the assumed body weight for each cohort, change in height, impacts the how influential energy surplus and deficits are resulting in changes in the flows between BMI categories.
Change in Male height input assumptions
Change in Female height input assumptions
Growth Function kJ/day
Changes in the assumption Kj/day needed for growth resulting in relatively small changes in the BMI outcomes. The largest impact occurred in adolescent age groups where the growth assumptions where the largest. The larger observed impact in males was in 9-11 year olds and 12-15 year olds, where on average 1 Kj resulted in 0.2% change in the outcome.
Macro nutrients Kj per gram
Each of the food groups are broken down to the macro nutrients; carbohydrate, protein, fats and sugars. The energy from a gram of macronutrients is an model input. Since the input energy assumption for each macronutrient effect the energy for each food group to each age-gender-BMI group, all of the population. This creates highlight sensitivity assumptions.
- The input of macronutrient becomes more sensitive for older age group, this is due the the cumulative impact over the populations life course.
- Higher kJ/g leads to higher daily total dietary intake leading to higher prevalence of overweight and obesity.
- The lowest impact to overweight or obesity was 0.8%/kJ.
- The higher impact was 19.89%/kJ.
Example of interpretation
Thermic effect of food (TEF)
The themogenesis effect of food (TEF), is the proportion of the energy used for digestion. A higher TEF means less of the dietary energy is available after digestion. TEF input assumptions impacts whole population, translating to a highly sensitivity input assumption.
- Change in TEF, cumulative over the life course leading to a higher impact for older age groups.
- 1 unit change in the TEF of carbohydrate results in
a between 26.18 to 488.39 % change in prevalence of underweight and
healthy weight.
- Since TEF unit is a proportion, 1 unit change is too wide, a 0.1 unit change would result in a 2.6% to 48.84% change in the prevalence of underweight.
- 1 unit change in the TEF of Fat results in a
between 29.54 to 545.79 % change in prevalence of underweight and
healthy weight.
- a 0.1 unit change would result in a 2.95% to 54.58% change in the prevalence of underweight.
- 1 unit change in the TEF of Protein results in a
between 14.22 to 345.20 % change in prevalence of underweight and
healthy weight.
- a 0.1 unit change would result in a 1.42% to 34.52% change in the prevalence of underweight.
- 1 unit change in the TEF of Sugar results in a
between 38.45 to 533.02 % change in prevalence of underweight and
healthy weight.
- a 0.1 unit change would result in a 3.85% to 53.30% change in the prevalence of underweight.
Example of interpretation
Infant Reported behaviours
The assumed reported infant behaviours exemplifies the intergenerational effects. However these impacts are minimal.
- The proportion of mother that breast feed impact older age groups, this is because of the increase of energy expenditure caused by breastfeeding.
- The proportion of infants that either consume non-core foods and TV for greater then 1 hr/day impact younger age groups, higher non-core food consumption and greater TV viewing increases the prevalence of overweight and obesity.
Intergenerational OR effects
Mortality ratios
Hazard ratios are applied to exogenous mortality rate so predicted population dynamics are maintained.
- Changing these assumptions impact older age group, primarily cause by higher mortality rates in these age groups.
- Since the primary outcome is a percentage, these ratio have little impact.
METs
Duration and intensive (METs) of physical activity are both used in estimating total energy expenditure. The assumed METs for each of the movement categories is applied to all of the population, which results in highligh sensitivity input assumptions.
- Impact from variations in METs assumptions accumulate over the life cource of the population resulting in higher impacts for older age groups.
- Low MET values for sleep and inactivity aswell as high duration
results in high sensitivity.
- 1 unit increase in sleep METs results in a between 20.42% to 312.38% change in obesity.
- 1 unit increase in inactive METs results in a between 12.5% to 206.59% change in obesity.
- Other results;
- 1 unit increase in screen time METs results in a between 8.76% to 163.84% change in obesity.
- 1 unit increase in light physical activity METs results in a between 4.18% to 74.62% change in obesity.
- 1 unit increase in moderate physical activity METs results in a between 2.97% to 33.48% change in obesity.
- 1 unit increase in moderate physical activity METs results in a between 1.88% to 29.19% change in obesity.
LIGHT PA
Each behaviour is structure so that they are age dependent, observed surveyed behaviours were modelled using a linear regression with age groups as the independnet variable. This creates two variables for each behaviour, the intercept is the level of behaviour at the youngest age group (2 years old) and the change of behaviours over the life course.
- Changes in the intercept assumptions have cumulative impacts over the life course, resulting in higher impacts in older age groups compared to younger age groups.
- Variying age-on-age (AGE SLOPE) change the trajectory of behaviours over the life course, making older age group BMI outcomes sensitivity to changes in age slope.
- For each minute increase in the light physical activity intercept
prevalence can change 0.5%.
- the input assumptions range between 90 mins and 127 mins; a change in 10 mins results in 5% change in outcome.
- For each minute increase in the light physical activity age slope
prevalence can change 0.8%.
- the input assumptions range between 13 mins and 36 mins per age group; a change in 5 mins results in 4% change in outcome.
MODERATE PA
VIGOROUS PA
SCREEN TIME
SLEEP
Fruit Reported Intake
Vegetables Reported Intake
Grains Reported Intake
Dairy Reported Intake
Meat and Protein Reported
Discretionary foods Reported
Fats and Oils Reported
Sugar based beverage Reported
Water Reported
Initial FM %
Change in Male height input assumptions
Change in Female height input assumptions
Proportion of nutrients within food group Inputs
Grains
Vegetables
Fruit
Dairy
Meat
Fats
Discretionary foods
Miscellaneous (Other)
Non-sugar-sweetened beverages
Sugar-sweetened beverages
Initial BMI Prevalence Inputs
Change in Male Initial BMI Prevalence
Change in Female Initial BMI Prevalence